Microsoft Fabric Updates Blog

Create Embeddings in Fabric Eventhouse with built-in Small Language Models (SLMs)

What if generating embeddings in Eventhouse didn’t require an external endpoint, callout policies, throttling management, or per‑request costs? That’s exactly what slm_embeddings_fl() delivers: a new user-defined function (UDF) that generates text embeddings using local Small Language Models (SLMs) from within the Kusto Python sandbox, returning vectors that you can immediately use for semantic search, similarity … Continue reading “Create Embeddings in Fabric Eventhouse with built-in Small Language Models (SLMs)”

ML Model Scoring in Fabric Eventhouse via Update Policy

In this blog post, we will describe how to train an ML model in Fabric Spark notebook, save it in Fabric’s models registry and use it for scoring new streaming data by Fabric Eventhouse via update policy in real time. We describe a typical workflow that can be implemented to monitor cloud resources or IoT … Continue reading “ML Model Scoring in Fabric Eventhouse via Update Policy”

Advanced Time Series Anomaly Detector in Fabric

Anomaly Detector, one of Azure AI services, enables you to monitor and detect anomalies in your time series data. This service is based on advanced algorithms, SR-CNN for univariate analysis and MTAD-GAT for multivariate analysis and is being retired by October 2026. In this blog post we will lay out a migration strategy to Microsoft Fabric, allowing … Continue reading “Advanced Time Series Anomaly Detector in Fabric”